Nonequilibrium protein complexes as molecular automata

TL;DR

This paper models protein complexes as nonequilibrium molecular automata, revealing their potential for error-tolerant memory and computation, and providing a framework for engineering synthetic molecular automata.

Contribution

It introduces a thermodynamically-consistent model linking protein complexes to stochastic cellular automata for molecular computation.

Findings

Protein complexes can function as molecular automata with error-tolerant memory.

Long transients in these systems can serve as molecular stopwatches.

All possible dynamical rules were systematically enumerated to identify computational capabilities.

Abstract

Biology stores information and computes at the molecular scale, yet the ways in which it does so are often distinct from human-engineered computers. Mapping biological computation onto architectures familiar to computer science remains an outstanding challenge. Here, inspired by Crick's proposal for molecular memory, we analyse a thermodynamically-consistent model of a protein complex subject to driven, nonequilibrium enzymatic reactions. In the strongly driven limit, we find that the system maps onto a stochastic, asynchronous variant of cellular automata, where each rule corresponds to a different set of enzymes being present. We find a broad class of phenomena in these 'molecular automata' that can be exploited for molecular computation, including error-tolerant memory via multistable attractors, and long transients that can be used as molecular stopwatches. By systematically enumerating all possible dynamical rules, we identify those that allow molecular automata to implement simple computational architectures such as finite-state machines. Overall, our results provide a framework for engineering synthetic molecular automata, and offer a route to building protein-based computation in living cells.